Polymers obtained from renewable raw materials are a valuable group of compounds that are used in many industries, including the pharmaceutical industry. With the growing interest in biopolymers, there is a need to find new natural monomers that can replace petroleum-based raw materials. One of such natural compounds is betulin, a pentacyclic triterpene, that occurs in nature, e.g. in the outer layer of birch bark. Both betulin and its derivatives e.g. betulin disuccinate, exhibit a broad spectrum of biological activity, including anti-cancer activity, while being non-toxic to normal cells. The aim of this study was to obtain a new, biodegradable betulin-based polyanhydrides exhibiting anti-cancer activity. Polyanhydrides were obtained by melt polycondensation of betulin disuccinate and sebacic acid with the use of acetic anhydride. Mentioned polyanhydrides were then thoroughly characterized by ¹H NMR and ¹³C NMR, size exclusion chromatography, differential scanning calorimetry and FT-IR spectroscopy. The content of sebacic acid in obtained copolymers was from 20 to 80 wt %. The use of sebacic acid as a comonomer increases the crystallinity of polymers. Polymers were used for the preparation of microspheres using emulsion (O/W) solvent evaporation technique. Under physiological conditions copolymers undergo hydrolytic degradation to betulin disuccinate, whose biological activity is known and confirmed and to sebacic acid approved by FDA for use in drug delivery systems. Polyanhydrides were also tested for cytostatic activity against a wide range of cancer cell lines (HeLa, MCF-7, A-549, U-87MG, KB and HepG2), proving its efficiency in inhibiting the growth of selected cell lines.

The blood-brain barrier (BBB) is a physiological barrier that actively interacts between the circulatory system and the Central nervous system. Simulating the functioning of the BBB is one of the most important tasks. The result will have significance for not only fundamental science but also for applied science. It is known that the physiological permeability of the BBB is disturbed in various pathologies of the Central nervous system (ischemia, brain hypoxia, injuries and tumors, neurodegenerative diseases). Changes in permeability are selective and often with ineffective pharmacotherapy. Therefore, if scientists can simulate the barrier, they can conduct optimal studies of the efficiency of drugs. The simulated barrier is composed of membranes and three types of basic cells, astrocytes, endothelial cells, and pericytes. Several requirements are imposed on the membrane, such as the passage of water and small molecules, formation of close contact with cells, and control of large molecules passage. In this work, we use gelatin-based film for BBB imitation due to its high biocompatibility. Since gelatin is initially water-soluble, we modified it with methacrylate groups to make it able for cross-linking. Four modified gelatin membranes that differ in the degree of cross-linking were obtained by varying the concentration of photoinitiator methacrylate groups and the time of UV radiation. The obtained membranes were used to study their biological properties, immunohistochemistry, cell proliferation, and morphometry. It was shown, that membrane with an average degree of cross-linking demonstrated the optimal properties for cell adhesion and proliferation.

When conducting AE testing, there is an industrial need to separate AE from monitoring area to that from outside of the area in some cases. In this study, usefulness of autoencoder to solve this problem is discussed by simple experiment using an isotropic thin steel ruler. It was shown that a single trained autoencoder can be used for separating AE signals with variety of waveforms from monitoring area to those from outside of monitoring area when setting an appropriate threshold.

Cities are major contributors to greenhouse gas emissions (GHG) due to high density of urbanization, numerous industrial centers and intensive agricultural activities. These anthropogenic GHG sources overlap to the sources of methane related to peat degradation or pockets of methane that characterize the outermost, NE-verging fronts of the Northern Apennines in Italy. This study focused on atmosphere and soil methane gas measurements close by an area with high density of abandoned wells used for the methane extraction back in 1962 in a small town of Italy. Radon gas was measured as well, simultaneously with the instruments for methane and oxygen gases, at 10 cm and 1 m depth into the soil. Measurements have been taken for radon concentrations with a Durridge RAD7 Company, Inc., USA instrument. Instead, three Biogas ETG (Etg Risorse e Tecnologia, Italy) instruments were used for atmosphere and soil gas measurements, with new low-cost technology, nondispersive infrared sensor (NDIR) CH₄ gas sensor and O₂ gas sensor. Moreover, chemical and physical properties of soil and water were checked at each location monitored. At a depth of 1 m below the ground surface, the maximum soil radon gas concentration was found to be around 1770 ±±582 Bq/m³, with soil consisted of 64.31% sand, 20.75% silt and 14.94% clay, and 0.526 ppm of Uranium. The maximum concentration of methane was found to be 0.06%, at a depth of 1 m into the soil characterized by 83% sand, 8.96% silt and 7.89% clay. The methane gas measurement survey presented generally values on the range of 0.01% to 0.03% into the soil and no significant relationship existed between methane and oxygen concentrations.

The changes in land surface temperature (LST) concerning time and space are mapped with the help of satellite remote sensing techniques. These measurements are used for determining several geophysical parameters including soil moisture, evapotranspiration, thermal inertia, and vegetation water stress. This study aims at calculating and analyzing the LST of manmade and natural features of Doon Valley, Uttarakhand, India. The study area includes the forest range of Doon Valley, agricultural areas, and urban settlements. Spaceborne multitemporal thermal bands of Landsat 8 were used to calculate the LST of various features of the study area. Split window algorithm and emissivity-based algorithms were tested on the Landsat-8 data for LST calculation. The study also explored the effect of atmospheric correction on the temperature calculation. The land surface temperature determined using an emissivity based method that did not provide atmospheric correction be found to less accurate as compared to the results by the split-window method. The LST for urban settlements is higher than the forest cover. A temporal analysis of the data shows an increase in the average temperature. The study shows the potential of spaceborne thermal sensors for the multitemporal analysis of the LST measurement of manmade and natural features.

Ultrasonic monitoring of cementitious media during hydration is useful since parameters like wave velocity and amplitude are influenced by the developing stiffness of the medium, allowing evaluation of the curing stage and elastic modulus in real time. However, wave propagation in such a heterogeneous system is very complicated due to different constituents, as well as the several length scales of the heterogeneity, allowing only a rough interpretation behind the specific trends. In the present study, the ultrasonic velocity and attenuation are investigated in terms of the frequency. It is seen that the dispersion, being a result of the initial properties mismatch, is smoothened after setting for all the materials while simultaneously the attenuation significantly decreases. The model mixes include reference mortar, mortar with super-absorbent polymers and mortar with retarder. The effect of the admixtures is evident as SAPs delay the setting and the smoothening of the dispersion curve, while the retarder produces two types of phenomena: first the rapid “false setting” obvious by sudden change in dispersion and attenuation and delayed hydration. It is suggested that dispersive features of ultrasound can strongly enhance the characterization of fresh cementitious media.

Purpose. To assess the quantity of exposed dentin detected by 3 operators for 2 different geometries of tooth preparations, window (WI) and butt-joint (BJ).

Methods. 20 intact maxillary central incisors were collected. One prosthodontist prepared the specimens for porcelain laminate veneers to a depth of 0.6 mm, with a cervical chamfer-line of 0.3 mm, using a silicone index. Subsequently, each prepared tooth was analyzed by 3 operators with different clinical experience, student (ST), medium experienced (ME), and expert (EX) to calculate the percentage of exposed dentin at sight under magnification. In addition to descriptive statistics (CI 95%), a 2-way ANOVA and the Games-Howell test were used to analyze differences among groups (α=.05).

Results. The means of the calculated percentages of dentin exposure were: WI=30.48%; BJ=30.99%; ST/WI=22.82%; ME/WI=58.05%; EX/WI=10.55%; ST/BJ=28.99%; ME/BJ=40.56%; EX/BJ=23.42%.

The 2-way ANOVA detected significant differences among operators (p<.001) but not between WI and BJ (p=.898). The Games-Howell test detected differences between ST/WI and ME/WI (p=.005) and between ME/WI and EX/WI (p<.001).

Conclusions. There is no difference in the detection of exposed dentine among operators with different expertise for BJ preparation, whereas differences were detected between ME and the other 2 operators in the WI preparation.

The mean values of exposed dentin found in WI and BJ were approximate of 30%, falling within the ideal range of enamel preservation (50%-70%) to achieve optimal adhesion. Moreover, the quantity of exposed dentin is not related to different tooth preparation geometry.

Tracheal sound represents an easily acquired and processed signal that is particularly popular in the evolution of smartphone-based systems for Sleep Apnea Syndrome (SAS) diagnosis. SAS is characterized by partial or complete breath cessation for at least 10 s. The developed algorithms mainly rely on neural networks focusing on the Apnea/Hypopnea Index (AHI) extraction; this index corresponds to the apneic episodes’ count per sleeping hour. Though reported accurate in AHI estimation, neural networks are severely affected by the inter- and intra-patient breathing sound variability. Alternatively, breathing detection algorithms can contribute in identifying the dominant sound patterns within the apnea event. Similar works propose silence detection to locate apnea onset, eventually neglecting hypopnea, often accompanied by snoring. In this work, we employ four features: zero-crossing rate, signal power, Tsallis entropy and Shannon information to discriminate breathing from silent frames. These features are extracted independently by tracheal sound recordings from 178 patients undergoing a sleep study. A candidate apnea corresponds to silence detected by at least one feature for a minimum duration of 5 s. Additionally, a reduction of the mean signal power, in the detected breathing frames, is indicative of hypopnea. The algorithm presents a maximum sensitivity per patient 98.75 % and it can locate the end of 80.45 % of all annotated episodes (32824 out of 40800) with an error less than 10 s. Despite the non-negligible number of false positive detections, the proposed algorithm proves the dominance of the described sound pattern in the majority of the apnea/hypopnea episodes.

Aim: Bulk-fill resin composites have a high depth of cure, and cavity with a depth even higher than 4 mm can be restored though a single step with the bulk-fill technique. A main concern of bulk-fill composites is the shrinkage stress developing at the composite-tooth walls interface, potentially higher than that developed through the incremental layering technique. The aim of this study is to investigate cusps deformation caused by material shrinkage during photopolymerization.
Materials and Methods: Two bulk-fill composite materials, with high-viscosity and low-viscosity and a different material composition, were characterised through linear shrinkage and compressive tests. Using both the bulk-fill and the incremental layering techniques for the restoration of mesio-occlusal-distal cavities of human premolars, cusps distance variation was evaluated.
Results: The low-viscosity composite presents a significantly higher shrinkage value (p<0.05) than the high-viscosity composite, while mechanical properties such as strength and the Young’s modulus of the high-viscosity composite are significantly higher (p<0.05). No significant difference has been observed for cusps deformation in both the composite materials according to mesio-occlusal-distal cavities restored through the bulk-fill or the incremental layering techniques.
Conclusions: Although for the high-viscosity composite, a lower cusps deformation would be expected, no significant difference has been observed between the composite materials. This result can be ascribed to the higher Young’s modulus value of the high-viscosity composite. This suggests that the high-viscosity composite is stiffer, while the low-viscosity composite is more compliant, thus balancing the cusps distance variation.

The use of efficient, durable and low-impact processes for the environment is highly desirable to synthesize nanomaterials for various applications. A new approach is presented to synthesize nanoparticles on different powder substrates. The process is based on the plasma degradation of solid organometallic precursors mixed with the powder substrate in order to generate e.g. new catalytic systems. Compared to conventional wet chemistry, plasma processing offers the advantage of reducing the environmental impact of the synthesis by reducing the energy consumption and relying on a solvent-free and waste-free scalable process. The novelty and high versatility of the process is demonstrated in this work. Choosing the right discharge parameters (pressure, reactive gas , plasma power,…), amorphous or crystalline monometallic, bimetallic, oxide or nitride nanoparticles can be produced, onto inorganic (such as TiO₂) or carbon-based substrates like graphene, carbon xerogel or carbon nanotubes. Results have been obtained for various nanoparticles, including transition (Mn, Fe, Ni), post transition (Zn, Al), and noble metals (Cu, Pt, Pd, Rh). Moreover, the organometallic precursor(s) decomposition and the subsequent nanoparticles synthesis can be monitored in situ using optical emission spectroscopy of the plasma discharge. Applications in photocatalysis, magnetic materials, or catalysts for fuel cells are demonstrated.